[Prospective,multi-center,and large-scale hospital centralized monitoring of clinical safety of Reduning Injection in 100249 children cases].

This study utilized a prospective, large-sample, multi-center, and registered key specialty approach of hospitals to monitor the application of Reduning Injection. A total of 100 249 adolescent patients aged 14 years and below who received Reduning Injection were monitored, resulting in 83 cases of adverse events, with 76 of them being classified as adverse drug reaction(ADR). The calculated incidence rate of ADR for Reduning Injection was 0.076%, indicating a very rare ADR. The main symptoms of ADR were pruritus, diarrhea, abdominal pain, vomiting, high fever, dyspnea, convulsion, and chills. All ADR cases were reported for the first time, including three new ADR cases and 73 known ADR cases. The categories of ADR was general ADR. All ADR was mild in severity. There were more males than females in ADR patients. One patient had a history of ADR, and the drug causing ADR was buprofen. The largest number of ADR cases occurred when the dosage of Reduning injection was 5-10 mL. The dropping speed was 30 drops or less per min, and the solvent type was 5% glucose injection. The most common manifestation of ADR patients was pruritus, followed by diarrhea, abdominal pain, vomiting, high fever, dyspnea, convulsions, and chills. 72 patients(94.74% of ADR patients) discontinued the drug, and three patients(3.95% of ADR patients) were given oxygen inhalation. 47 cases(61.84% of ADR patients) were treated with medication, of which dexamethasone was the most used(24 cases, 46.15% of ADR patients). 76 ADR patients were cured or improved. ADRs are more likely to occur when diagnosed with acute bronchitis by western medicine and cough by traditional Chinese medicine(TCM), TCM syndrome type is wind heat syndrome, and the combination medicine is ambroxol hydrochloride and bromhexine hydrochloride injection, ascorbic acid/vitamin C injection. This result provides an evidence-based safety basis for active pharmacovigilance of Reduning Injection in adolescents aged 14 years and below.

Efficacy of Prednisone Avoidance in Patients With Liver Transplant Using the U.S. Food and Drug Administration Adverse Event Reporting System.

Background Immunosuppressants are administered in various combinations to prevent immune-induced transplant rejection in patients with liver transplant, as each immunosuppressant acts on different cellular sites. However, the use of multiple immunosuppressants also increases the risk for adverse events. Therefore, it is desirable to reduce the types of immunosuppressants administered without increasing the incidence of transplant rejection. The effectiveness of prednisone avoidance has been suggested, although this was not based on statistical significance in many instances. To definitively establish the effectiveness of prednisone avoidance, a statistically significant difference from a prednisone-use group should be demonstrated. Additionally, the effectiveness of prednisone avoidance might vary depending on the combination of other immunosuppressants administered. It has therefore been considered necessary to investigate, for various immunosuppressant combinations, the administration patterns in which prednisone avoidance is effective. Objectives This study aimed to investigate the effectiveness of prednisone avoidance in patients with liver transplant and discuss the results based on statistically significant differences. Methods Data from the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) were obtained. In studying immunosuppressant combinations, it was essential to control for confounding. Thus, the immunosuppressant combinations, excluding prednisone, were kept the same in the two groups being compared (prednisone-use and prednisone-avoidance groups). The large sample from FAERS allowed for those various immunosuppressant combinations to be compared. Comparisons of transplant rejection in the prednisone-use and prednisone-avoidance groups used the reporting odds ratio (ROR) and the adjusted ROR (aROR), which controlled for differences in patient background. Results With the prednisone-use groups being set as the reference, ROR and aROR were calculated for the prednisone-avoidance groups. Various immunosuppressant combinations were evaluated, and in four patterns - (1) the combination of prednisone and tacrolimus, (2) the combination of prednisone, cyclosporine, and tacrolimus, (3) the combination of prednisone, tacrolimus, and basiliximab, and (4) the combination of prednisone and everolimus) - both the ROR and the aROR for transplant rejection in the prednisone-avoidance group were significantly <1.000. Conclusions This study identified effective immunosuppressant combinations for prednisone avoidance that were not associated with increased transplant rejection. The evidence supporting the effectiveness of prednisone avoidance is strengthened when combined with results from previous studies.

Analysis of Adverse Events Following Phenobarbital Administration for Pediatric Patients Categorized by One-Year Age Increments Using the U.S. Food and Drug Administration Adverse Event Reporting System.

Background Organ and body development greatly varies in pediatric patients from year to year. Therefore, the incidence of each adverse event following phenobarbital (PB) administration would vary with age. However, in clinical trials, increasing the sample size of pediatric patients in each age group has been challenging. Therefore, previous studies were conducted by dividing pediatric patients into three or four age groups based on the development stage. Although these results were useful in clinical settings, information on adverse events that occurred at one-year age increments in pediatric patients could further enhance treatment and care. Objectives This study investigated in one-year age increments the occurrence tendency of each adverse event following PB administration in pediatric patients. Methods This study used data obtained from the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS). Two inclusion criteria were set: (1) treatment with PB between January 2004 and June 2023 and (2) age 0-15 years. Using the cutoff value obtained using the Wilcoxon-Mann-Whitney test by the minimum p-value approach, this study explored changes in the occurrence tendency of each adverse event in one-year age increments. At the minimum p-value of <0.05, the age corresponding to this p-value was determined as the cutoff value. Conversely, at the minimum p-value of ≥0.05, the cutoff value was considered nonexistent. Results This study investigated all types of adverse events and explored the cutoff value for each adverse event. We identified 34, 16, 15, nine, five, five, eight, three, and eight types of adverse events for the cutoff values of ≤3/>3, ≤4/>4, ≤5/>5, ≤6/>6, ≤7/>7, ≤8/>8, ≤9/>9, ≤10/>10, and ≤11/>11 years, respectively. Conclusions This study demonstrated that adverse events requiring attention in pediatric patients varied with age. The findings help in the improvement of treatment and care in the pediatric clinical settings.

Early heart rate fluctuation and outcomes in critically ill patients with sepsis: A retrospective cohort study of the MIMIC-IV database.

Background: Heart rate (HR) abnormalities are common in critically ill patients, but the significance of HR fluctuation in sepsis remains unclear. We aimed to assess the association of HR fluctuation with intensive care unit (ICU) mortality, hospital mortality, and 28-day mortality in patients with sepsis and identify the cutoff value of HR fluctuation associated with the lowest risk of death. Methods: We conducted a retrospective cohort study using the medical information mart for the intensive care IV database. HR fluctuation, defined as the difference between maximum and minimum HR within the first 24 h of ICU admission, was analyzed for its association with outcomes using restricted cubic spline and multivariable Cox regression models. Results: Among 24,419 eligible patients with sepsis, HR fluctuation showed a J-shaped association with ICU mortality, hospital mortality, and 28-day mortality. The high HR fluctuation group (≥ 35 bpm) had a significantly increased risk of ICU mortality ([hazard ratio, 95% confidence interval] 1.12,1.02-1.22, P = 0.013), hospital mortality (1.10,1.02-1.19, P = 0.013), and 28-day mortality (1.11,1.03-1.20, P = 0.007) compared to the control group (HR fluctuation 25-34 bpm). The low HR fluctuation group (< 25 bpm) showed no significant difference in the risk of mortality compared to the control group. Conclusions: Our large-sample study suggests that early high HR fluctuation is indicative of poor prognosis in critically ill patients with sepsis. Early HR fluctuation may serve as a readily available "high-risk alert system" influencing therapeutic decision-making.

A correlation study of music training, adult attachment, and personality traits using a large-sample questionnaire.

Introduction: Music training can provide benefits to psychological health and is strongly associated with adult attachment style and personality traits through bidirectional interactions. Methods: A large sample including 10,191 Chinese musicians and non-musicians completed the Relationship Questionnaire and Big-Five Personality Inventory. Results: Connections between music training, adult attachment, and personality were analyzed with the following results: (1) personality traits were correlated with attachment dimensions, with positive correlations between secure attachment and extroversion and between dismissing attachment and neuroticism; (2) music training was connected with the secure and fearful-avoidant attachment dimensions, which complemented the effect of educational level in the preoccupied and dismissing dimensions; (3) music training enhanced extroversion, openness, agreeableness, and conscientiousness, which interacted to affect extroversion and openness by gender; and (4) music training enhanced the regression of extroversion to preoccupied and secure attachments, and the regression of openness to preoccupied attachment. Discussion: Conclusively, music training enhanced the connection between secure attachment and positive personality traits and regulated the correlation between insecure attachment and neuroticism. This analysis provides a large sample of statistical and practical evidence for the clinical practices of mental health and the educational and music training practices of co-cultivating cultural knowledge and artistic quality.

The Causal Effects of Cholelithiasis on Acute Pancreatitis and Pancreatic Cancer: A Large Sample Size Mendelian Randomization Analysis.

BACKGROUND: The aim of two-sample Mendelian randomization (MR) with a large sample size was to explore the causal cholelithiasis impact on acute pancreatitis and pancreatic cancer. METHODS: We performed the two-sample MR analysis with two models. Publicly available summary- level information for cholelithiasis was acquired from the Genome-Wide Summary Association Studies (GWAS) of FinnGen Biobank. The inverse variance weighted (IVW) method was the main method to obtain the MR estimates. Other methods were also used as supplementary methods, including MR-Egger, maximum likelihood, MR-Robust Adjusted Profile Score (MR-RAPS), weighted median, penalised weighted median method, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) method. RESULTS: After the selection of genetic instrumental variables (IVs), 11 single nucleotide polymorphisms (SNPs) (Model 1) and 22 SNPs (Model 2) were used to explore the effect of cholelithiasis on acute pancreatitis, and 10 SNPs (Model 1) and 24 SNPs (Model 2) on pancreatic cancer. The findings obtained by the fixed-effect IVW method with both Model 1 and Model 2 showed that genetically predicted cholelithiasis was significantly related to the elevated acute pancreatitis risk (Model 1: OR: 1.001, 95% CI: 1.000-1.002, p <0.001; Model 2: OR: 1.001, 95% CI: 1.000-1.002, p <0.001). Moreover, cholelithiasis would also raise the pancreatic cancer risk (Model 1: OR: 1.676, 95% CI: 1.228-2.288, p = 0.001; Model 2: OR: 1.432, 95% CI: 1.116-1.839, p = 0.005). CONCLUSION: Genetically predicted cholelithiasis was significantly related to the elevated risk of acute pancreatitis and pancreatic cancer. More attention should be paid to patients with cholelithiasis for the primary prevention of pancreatic-related diseases.

Model detection for semiparametric accelerated failure additive model with right-censored data.

Censored data frequently appeared in applications across a variety of different areas like epidemiology or medical research. Traditionally statistical inference on this data mechanism was based on some pre-assigned models that will suffer from the risk of model-misspecification. This article proposes a two-folded shrinkage procedure for simultaneous structure identification and variable selection of the semiparametric accelerated failure additive model with right-censored data, in which the nonparametric functions are addressed by spline approximation. Under some regularity conditions, the consistency of model structure identification is theoretically established in the sense that the proposed method can automatically separate the linear and zero components from the nonlinear ones with probability approaching to one. Detailed issues in computation and turning parameter selection are also discussed. Finally, we illustrate the proposed method by some simulation studies and two real data applications to the primary biliary cirrhosis data and skin cutaneous melanoma data.

Clinical analysis of 2790 children with retinoblastoma: a single-center experience in China.

BACKGROUND: In this study, we aimed to analyze the clinical characteristics and prognosis of children with retinoblastoma (RB) in a single center in China with a large sample collection spanning 17 years. METHODS: The clinical data of 2790 children with RB treated in Beijing Tongren Hospital from 2005 to 2021 were collected, and a retrospective analysis was conducted. RESULTS: The median age of the participants was 28.3 months. There were 3624 affected eyes, 12.4% of which were in groups A-C, 67.1% in groups D-E and 16.2% were not specified. The primary symptom observed in most cases was a white pupil, accounting for 66.5%, followed by strabismus (12.8%). The median follow-up time was 59.7 months. The enucleation rate was 71.3% (703/986) in a single left eye and 72.5% (702/968) in a single right eye. The overall survival (OS) rate was 95.8% (2444/2552) because 237 patients dropped out, and 109 died. Kaplan‒Meier survival analysis showed that the median survival time (MST) was 125.92 months [95% confidence interval (CI) = 124.83-127.01]. Cox multivariate survival analysis showed that trilateral RB (P = 0.017), metastasis site (P = 0.001), and combined distant tissue metastasis (P = 0.001) were independent prognostic factors for RB. The OS of 44 cases of familial RB was 93.2% (41/44), with an MST of 80.62 months (95% CI = 67.70-93.54). CONCLUSIONS: The timing of eye protection treatment and enucleation should be comprehensively judged to avoid worsening prognosis due to operation time delay. More importantly, the promotion and popularization of diagnosis and treatment technologies are necessary to further improve RB prognosis.

Confidence intervals for ratios of means applied to corpus-based word frequency classes.

The words we choose when we communicate with one another convey meaning and information. In written or spoken language, we tend to employ a relatively small number of words repeatedly whereas a large number of words in the lexicon are seldom used. By considering a ratio of means of the most prevalent word in a body of texts (or corpus) compared to that of the word in question, one can quantify the prevalence of the word in question. Furthermore, the concept of word classes or grouping words having similar measures of prevalence enables the investigator to compare the words. Using a sample of texts having varying lengths from a corpus, the sample mean relative frequency of a word and the maximum likelihood estimator using the zero-inflated beta distribution serve as two measures of the prevalence of a word. We construct and then compare asymptotic confidence intervals involving ratios of means for a number of words in the British National Corpus, a 100 million-word collection of written and spoken language of a wide range of British English. We also examine the sample sizes required to meet specific objectives regarding word classes and ratios of means.

Biological studies with comprehensive 2D-GC-HRMS screening: Exploring the human sweat volatilome.

A key issue in GCxGC-HRMS data analysis is how to approach large-sample studies in an efficient and comprehensive way. We have developed a semi-automated data-driven workflow from identification to suspect screening, which allows highly selective monitoring of each identified chemical in a large-sample dataset. The example dataset used to illustrate the potential of the approach consisted of human sweat samples from 40 participants, including field blanks (80 samples). These samples have been collected in a Horizon 2020 project to investigate the capacity of body odour to communicate emotion and influence social behaviour. We used dynamic headspace extraction, which allows comprehensive extraction with high preconcentration capability, and has to date only been used for a few biological applications. We were able to detect a set of 326 compounds from a diverse range of chemical classes (278 identified compounds, 39 class unknowns, and 9 true unknowns). Unlike partitioning-based extraction methods, the developed method detects semi-polar (log P < 2) nitrogen and oxygen-containing compounds. However, it is unable to detect certain acids due to the pH conditions of unmodified sweat samples. We believe that our framework will open up the possibility of efficiently using GCxGC-HRMS for large-sample studies in a wide range of applications such as biological and environmental studies.

Relationship between lifestyle and metabolic factors and carotid atherosclerosis: A survey of 47,063 fatty and non-fatty liver patients in China.

Background and aims: Carotid atherosclerosis and stenosis are common lesions of the artery wall that form the basis of cardiovascular events. Compared with coronary atherosclerosis, few studies have explored the influencing factors of carotid atherosclerosis. The aim of this study was to explore the influencing factors of carotid atherosclerosis and carotid stenosis without and with fatty liver disease (FLD). Methods: A total of 47,063 adults were recruited for this cross-sectional study. The color Doppler ultrasound, including metabolic factors and lifestyle surveys, was used to determine whether the participants had FLD and carotid artery disease. Multiple logistic regression was used to investigate the influencing factors of lifestyle and metabolism of carotid atherosclerosis and stenosis in the participants with and without FLD. Results: In participants without FLD, current alcohol consumption (OR: 0.749, 95% CI: 0.588) and hip circumference (OR: 0.970, 95% CI: 0.961, 0.979) were the main protective factors for carotid atherosclerosis. Systolic blood pressure (OR: 1.022, 95% CI: 1.019, 1.025) and diastolic blood pressure (OR: 1.005, 95% CI: 1.001, 1.010), elevated fasting blood glucose (OR: 1.012, 95% CI: 1.005, 1.019), and non-sedentary behavior (OR: 1.084, 95% CI: 1.014, 1.160) were the main risk factors for carotid atherosclerosis. Hip circumference (OR: 0.932, 95% CI: 0.910, 0.954) and low-density lipoprotein (OR: 0.979, 95% CI: 0.964, 0.994) were protective factors for carotid stenosis. Smoking (OR: 3.525, 95% CI: 1.113, 11.169) and unqualified exercise (OR: 1.402, 95% CI: 1.083, 1.815) were risk factors for carotid stenosis. In participants with FLD, smoking (OR: 0.827, 95% CI: 0.703, 0.973) and hip circumference (OR: 0.967, 95% CI: 0.958, 0.977) were the main protective factors for carotid atherosclerosis. BMI 18.5-23.9 (OR: 1.163, 95% CI: 1.002, 1.351), non-sedentary behavior (OR: 1.086, 95% CI: 1.009, 1.168), and waist circumference (OR: 1.030, 95% CI: 1.022, 1.038) were the main risk factors for carotid atherosclerosis. Conclusion: Based on a large-sample check-up population in China, this study investigated the influencing factors of carotid atherosclerosis and carotid stenosis in fatty liver and non-fatty liver patients and explored the influencing factors of metabolism and lifestyle, which were mainly focused on exercise, sedentary behavior, smoking, alcohol consumption, hip circumference, and blood pressure.

Prevalence and Correlational Factors of Suicidal Ideation and Suicide Attempts Among Chinese Adolescents.

This study's purpose was to (1) determine the prevalence of suicidality (i.e., suicidal ideation or suicide attempts) among adolescents in a city in Northeast China and (2) identify the correlational factors among adolescents with suicidality. A total of 69,519 adolescents from grades 5 to 12 in a city in Northeast China participated in the online investigation. Students completed a structured questionnaire to report their demographic information, psychological characteristics, and suicidality. Univariable and multivariable logistic regressions were applied to determine significant correlational factors associated with suicidal ideation (SI) and suicide attempts (SA). The prevalence of SI and SA among adolescents in the past 12 months was 13 and 4.8%, respectively. Multivariable logistic regression analyses found that the potential risk factors for SI and SA included female, non-nuclear family, higher subjective socioeconomic status, meaningless in life, depression, bullying perpetrator, negative parental rearing styles, lower self-esteem scores, hopelessness, and stressful life events. In order to improve the accuracy of suicide risk identification, a cumulative risk index was used. With the increase in the number of cumulative risks, the risk of SI and SA also increased. So the cumulative risk index was very valuable. The total prevalence of SI and SA among primary and middle school students was high. Preventive measures could be implemented according to the risk factors.

Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics.

High-dimensional limit theorems have been shown useful to derive tuning rules for finding the optimal scaling in random walk Metropolis algorithms. The assumptions under which weak convergence results are proved are, however, restrictive: the target density is typically assumed to be of a product form. Users may thus doubt the validity of such tuning rules in practical applications. In this paper, we shed some light on optimal scaling problems from a different perspective, namely a large-sample one. This allows to prove weak convergence results under realistic assumptions and to propose novel parameter-dimension-dependent tuning guidelines. The proposed guidelines are consistent with the previous ones when the target density is close to having a product form, and the results highlight that the correlation structure has to be accounted for to avoid performance deterioration if that is not the case, while justifying the use of a natural (asymptotically exact) approximation to the correlation matrix that can be employed for the very first algorithm run.

A Novel Data Sampling Driven Kalman Filter Is Designed by Combining the Characteristic Sampling of UKF and the Random Sampling of EnKF.

In order to improve the performance of the Kalman filter for nonlinear systems, this paper contains the advantages of UKF statistical sampling and EnKF random sampling, respectively, and establishes a new design method of sampling a driven Kalman filter in order to overcome the shortcomings of UKF and EnKF. Firstly, a new sampling mechanism is proposed. Based on sigma sampling with UKF statistical constraints, random sampling similar to EnKF is carried out around each sampling point, so as to obtain a large sample data ensemble that can better describe the characteristics of the system variables to be evaluated. Secondly, by analyzing the spatial distribution characteristics of the obtained large sample ensemble, a sample weight selection and assignment mechanism with the centroid of the data ensemble as the optimization goal are established. Thirdly, a new Kalman filter driven by large data sample ensemble is established. Finally, the effectiveness of the new filter is verified by computer numerical simulation experiments.

Sensitive identification of milk protein allergens using on-line combination of transient isotachophoresis/micellar electrokinetic chromatography and capillary isoelectric focusing in fused silica capillary with roughened part.

A method for on-line concentration of milk proteins from large sample volumes using combination of transient isotachophoresis (tITP) and micellar electrokinetic chromatography (MEKC) in fused silica capillary with an inner roughened part has been developed. The method utilizes reversible dynamic adsorption of proteins onto a thin layer of PEG 4000 on the roughened surface of the capillary. In addition, the tITP/MEKC method was combined with capillary isoelectric focusing (CIEF) for on-line concentration, separation, identification and sensitive determination of proteins in skimmed milk. The method allows analysis of up to 50 µL of sample. This study has focused on the four important whey proteins, bovine serum albumin (BSA), α-lactalbumin (α-LA), and two genetic variants of ß-lactoglobulin (ß-LG A and ß-LG B). The proteins were identified on the basis of their migration times and characteristic pI values. The pI values of BSA, α-LA, ß-LG A, and ß-LG B were determined as 4.7, 4.4, 5.1, and 5.2, respectively. Limits of detection for BSA, α-LA and both ß-LG variants were found as 1.2, 1.0 and 1.0 pg mL-1, respectively. The linearity of calibration curves was characterized by the R2 = 0.9982. The method provided highly reproducible results as the relative standard deviations of the migration times and peak areas of the examined proteins did not exceed 1.6%.

Two community types occur in gut microbiota of large-sample wild plateau pikas (Ochotona curzoniae).

Studies on large-sample gut microbial sequencing data indicate that gut microbiota can be divided into multiple community types; different community types may influence the community function and ecosystem service. However, the knowledge on the classification, diversity, interaction, and assembling of microbial community types in the gut of wild animals is still insufficient. Here, we used pika gut microbiota data as an example to study the microbial community types in large-sample sequencing dataset. Cecal microbial communities from 118 wild plateau pika (Ochotona curzoniae) individuals at 5 elevational regions on the Qinghai-Tibet Plateau were analyzed. Our results show that pika gut microbiota can be separated into 2 community types (Cluster I and Cluster II). Cluster I was mainly distributed on the high-elevation regions with more than 3694 m and was most dominated by Firmicutes. Cluster II was from the low-elevation areas (lower than 3580 m), and was predominated by Bacteroidetes. Cluster I had a higher community alpha-diversity and predicted functional diversity than Cluster II, and the beta-diversity and predicted functional profiles of these 2 clusters were significantly different. Network analysis revealed that there were more complex interactions between Cluster I, which had enhanced influence on the co-occurrences of other microbes in the bacterial community when compared to Cluster II. Phylogenetic analysis found that the environmental filtering in the Cluster I was stronger than Cluster II. The assemblages of pika gut bacterial communities were determined mainly by deterministic processes, while the relative importance of deterministic processes accounted for more percentages in the Cluster I than Cluster II. Our results demonstrated that 2 gut microbial community types in pikas had distinct diversity patterns and ecological functions. Current methods are also helpful for identifying gut community types and the related mechanisms behind gut microbiota types in large-sample sequencing data of wild animals.

Comparative Proteome Signatures of Trace Samples by Multiplexed Data-Independent Acquisition.

Single-cell transcriptomics has revolutionized our understanding of basic biology and disease. Since transcript levels often do not correlate with protein expression, it is crucial to complement transcriptomics approaches with proteome analyses at single-cell resolution. Despite continuous technological improvements in sensitivity, mass-spectrometry-based single-cell proteomics ultimately faces the challenge of reproducibly comparing the protein expression profiles of thousands of individual cells. Here, we combine two hitherto opposing analytical strategies, DIA and Tandem-Mass-Tag (TMT)-multiplexing, to generate highly reproducible, quantitative proteome signatures from ultralow input samples. We developed a novel, identification-independent proteomics data-analysis pipeline that allows to quantitatively compare DIA-TMT proteome signatures across hundreds of samples independent of their biological origin to identify cell types and single protein knockouts. These proteome signatures overcome the need to impute quantitative data due to accumulating detrimental amounts of missing data in standard multibatch TMT experiments. We validate our approach using integrative data analysis of different human cell lines and standard database searches for knockouts of defined proteins. Our data establish a novel and reproducible approach to markedly expand the numbers of proteins one detects from ultralow input samples.

Approximating the Operating Characteristics of Bayesian Uncertainty Directed Trial Designs.

Bayesian response adaptive clinical trials are currently evaluating experimental therapies for several diseases. Adaptive decisions, such as pre-planned variations of the randomization probabilities, attempt to accelerate the development of new treatments. The design of response adaptive trials, in most cases, requires time consuming simulation studies to describe operating characteristics, such as type I/II error rates, across plausible scenarios. We investigate large sample approximations of pivotal operating characteristics in Bayesian Uncertainty directed trial Designs (BUDs). A BUD trial utilizes an explicit metric u to quantify the information accrued during the study on parameters of interest, for example the treatment effects. The randomization probabilities vary during time to minimize the uncertainty summary u at completion of the study. We provide an asymptotic analysis (i) of the allocation of patients to treatment arms and (ii) of the randomization probabilities. For BUDs with outcome distributions belonging to the natural exponential family with quadratic variance function, we illustrate the asymptotic normality of the number of patients assigned to each arm and of the randomization probabilities. We use these results to approximate relevant operating characteristics such as the power of the BUD. We evaluate the accuracy of the approximations through simulations under several scenarios for binary, time-to-event and continuous outcome models.

Choosing Interim Sample Sizes in Group Sequential Designs.

This manuscript investigates sample sizes for interim analyses in group sequential designs. Traditional group sequential designs (GSD) rely on "information fraction" arguments to define the interim sample sizes. Then, interim maximum likelihood estimators (MLEs) are used to decide whether to stop early or continue the data collection until the next interim analysis. The possibility of early stopping changes the distribution of interim and final MLEs: possible interim decisions on trial stopping excludes some sample space elements. At each interim analysis the distribution of an interim MLE is a mixture of truncated and untruncated distributions. The distributional form of an MLE becomes more and more complicated with each additional interim analysis. Test statistics that are asymptotically normal without a possibly of early stopping, become mixtures of truncated normal distributions under local alternatives. Stage-specific information ratios are equivalent to sample size ratios for independent and identically distributed data. This equivalence is used to justify interim sample sizes in GSDs. Because stage-specific information ratios derived from normally distributed data differ from those derived from non-normally distributed data, the former equivalence is invalid when there is a possibility of early stopping. Tarima and Flournoy [3] have proposed a new GSD where interim sample sizes are determined by a pre-defined sequence of ordered alternative hypotheses, and the calculation of information fractions is not needed. This innovation allows researchers to prescribe interim analyses based on desired power properties. This work compares interim power properties of a classical one-sided three stage Pocock design with a one-sided three stage design driven by three ordered alternatives.

Electroencephalography Correlates of Well-Being Using a Low-Cost Wearable System.

Electroencephalography (EEG) alpha asymmetry is thought to reflect crucial brain processes underlying executive control, motivation, and affect. It has been widely used in psychopathology and, more recently, in novel neuromodulation studies. However, inconsistencies remain in the field due to the lack of consensus in methodological approaches employed and the recurrent use of small samples. Wearable technologies ease the collection of large and diversified EEG datasets that better reflect the general population, allow longitudinal monitoring of individuals, and facilitate real-world experience sampling. We tested the feasibility of using a low-cost wearable headset to collect a relatively large EEG database (N = 230, 22-80 years old, 64.3% female), and an open-source automatic method to preprocess it. We then examined associations between well-being levels and the alpha center of gravity (CoG) as well as trait EEG asymmetries, in the frontal and temporoparietal (TP) areas. Robust linear regression models did not reveal an association between well-being and alpha (8-13 Hz) asymmetry in the frontal regions, nor with the CoG. However, well-being was associated with alpha asymmetry in the TP areas (i.e., corresponding to relatively less left than right TP cortical activity as well-being levels increased). This effect was driven by oscillatory activity in lower alpha frequencies (8-10.5 Hz), reinforcing the importance of dissociating sub-components of the alpha band when investigating alpha asymmetries. Age was correlated with both well-being and alpha asymmetry scores, but gender was not. Finally, EEG asymmetries in the other frequency bands were not associated with well-being, supporting the specific role of alpha asymmetries with the brain mechanisms underlying well-being levels. Interpretations, limitations, and recommendations for future studies are discussed. This paper presents novel methodological, experimental, and theoretical findings that help advance human neurophysiological monitoring techniques using wearable neurotechnologies and increase the feasibility of their implementation into real-world applications.